Multi-label Classification

3 items

RESEARCHarXiv CS.CL·21d ago

Retrieval-Based Multi-Label Legal Annotation: Extensible, Data-Efficient and Hallucination-Free

The paper proposes casting multi-label legal annotation as a retrieval task, using frozen models and k-nearest neighbors to assign labels. This method achieves competitive accuracy and strong data efficiency across legal datasets, significantly reducing computational costs compared to fine-tuning large language models.

Multi-label Classification LLMs Legal AI Data efficiency

RESEARCHarXiv CS.CL·8d ago

Knowledge Graph-Enhanced Zero-Shot Topic Classification: A Multi-Strategy Comparative Study

This paper presents a zero-shot multi-label topic classification framework, systematically investigating how per-article knowledge graph augmentation affects its performance. The authors test eight methods across fifteen LLMs and eight multi-label datasets, finding that keyword-enhanced classification is the best performing method in the base framework.

Multi-label Classification LLMs Knowledge Graph Zero-Shot Topic Classification

RESEARCHDEV.to AI·5/10/2026

Learning Deep Latent Spaces for Multi-Label Classification

This research explores methods for learning deep latent spaces to enhance multi-label classification. It aims to represent data in a lower-dimensional, meaningful space for improved accuracy and efficiency.

Multi-label Classification deep learning learning machine learning